A robust AHP-DEA method for measuring the relative efficiency: An application of airport industry

Abstract

Measuring the relative efficiency of similar units has been an important topic of research among many researchers. Data envelopment analysis has been one of the most important techniques for measuring the efficiency of different units. However, there are some limitations on using such technique and some people prefer to use other methods such as analytical hierarchy process to measure the relative efficiencies. Besides, uncertainty in the input data is another issue, which makes some misleading results. In this paper, we present an integrated robust DEA-AHP to measure the relative efficiency of similar units. The proposed model of this is believed to capable of presenting better results in terms of efficiency compared with exclusive usage of DEA or AHP. The implementation of the proposed model is demonstrated for a real-world case study of Airport industry and the results are analyzed.}}

Providing a framework based on decision-making methods to assess safety risk in construction projects

“…The risk management process is a logical and systematic process that should include identifying, analyzing, assessing, and dealing with risk while considering the organization's background, conditions, and facilities [14], [17]. Having a list of risks existing in a certain type of project enables project managers to review the potential risks and assess the special conditions governing the ongoing project to determine which risks can greatly endanger their projects and how to deal with them [9]. In order to succeed, organizations must use risk management principles, one of the most important dimensions of which is human resources [18], [19].…”

“…In other words, any action performed or any decision made can be associated with risks [7], [8]. This is mainly due to our inability to guarantee the achievement of our desired result [9], [10]. Therefore, there is also danger wherever there is a risk since these dangers threaten the favorable results [11].…”

“…determining the weight of each index (W i ): in this regard, the more significant indicators had a higher weight (9). Stage 4: determining the alternative i distance from the ideal alternative (higher performance of each index), which is shown by (A*) (10).…”